JP2017532623A - System and method for tracking and identifying infection transmission - Google Patents

Abstract

The present disclosure represents systems and methods for determining the source of infectious disease transmission. Phylogenetic methods are used to determine the evolutionary history and replication rate of infectious disease isolates. The evolutionary distance and / or replication rate of an infectious disease isolate can be compared to other isolates. Based on a comparison of evolutionary distance and / or replication rate, a source of infectious disease transmission is determined.

Description

  A health-related infection (HAI) is a patient-acquired infection that is received during health treatment for a condition unrelated to the infection. An example of patient-acquired HAI is that a healthy patient admitted to a hospital for a surgical procedure to treat a hernia will subsequently develop a staphylococcal infection at the surgical site in the recovery ward.

  HAI in the medical literature is often referred to as nosocomial infection. According to a survey conducted by the CDC in 2011, approximately 1 in 25 of all hospitalized patients have HAI. Studies have estimated that there were approximately 721,000 HAIs. HAI causes or contributes to approximately 75,000 deaths each year.

  Nosocomial infections can cause severe pneumonia and infections of the urinary tract, bloodstream and other parts of the body. Many types are resistant to antibiotic attack, and antibiotic resistance spreads to Gram-negative bacteria that can infect people outside the hospital. In the United States, the most frequent types of hospital infections follow pneumonia (21.8%), surgical site infections (21.8%) and gastrointestinal infections (17.1%). (Magill SS, Edwards JR, Bamberg W et al., “Multistate Point-Prevalence Survey of Health Care-Associated Infections”, N Engl J Med 2014; 370: 1198-208.)

  According to a 2009 report by the CDC, HAI charged nearly $ 35 billion per year on American hospitals. Much of the cost is associated with longer patient stays, hospital partial isolation, and source discovery and eradication. It is believed that approximately 25.6% of HAI is provided by medical devices such as catheters and ventilators. The remaining infections are thought to be associated with surgical procedures and other sources in the hospital. There is a need to be able to track hospital-related infections and determine the source of transmission to reduce the number of additional infections. (“The Direct Medical Costs of Healthcare- Associated Infections in U.S. Hospitals and the Benefits of Prevention” by Scott II, R. D., CDC, March 2009.)

  According to an exemplary embodiment of the present invention, a method receives electronic data representative of an infectious disease isolate sequence, and at least one stored in the database with the electronic data representative of the infectious disease isolate sequence. Comparing a reference sequence to determine a variant between the infectious disease isolate sequence and the at least one reference sequence; and an evolutionary history of the infectious disease isolate based at least in part on the variant. Determining at least a portion of: a step of calculating a phylogenetic metric of the infectious disease isolate based at least in part on the evolutionary history; and the phylogenetic of the infectious disease isolate Comparing a metric and a phylogenetic metric of the at least one reference sequence; and the phylogenetic metric of the infectious disease isolate and the Determining whether the infectious disease isolate was transmitted by the first reservoir or the second reservoir based at least in part on the difference between the phylogenetic metrics of at least one reference sequence; Providing an indication of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir. The evolutionary distance can be calculated by the Juke-Cantor method.

  According to an exemplary embodiment of the present invention, a method uses at least one processing unit to store an array of infectious disease isolates stored in memory accessible by the at least one processing unit, and Comparing at least one reference sequence stored in a database accessible by one processing unit to determine a variant between the infectious disease isolate sequence and the at least one reference sequence; Determining the replication rate of the infectious disease isolate based at least in part on the variant using one processing unit; and the replication rate of the infectious disease isolate using the at least one processing unit; Comparing the replication rate of the at least one reference sequence with the replication rate of the infectious disease isolate and the Determining whether the infectious disease isolate has been transmitted by a first reservoir or a second reservoir based at least in part on the difference between at least one reference sequence and the replication rate; and Providing the user with a display using the display to determine whether the disease isolate has been transmitted by the first reservoir or the second reservoir. The first storage unit may be a living microorganism, and the second storage unit may be a non-biological region.

  According to an exemplary embodiment of the present invention, a method uses at least one processing unit to store an array of infectious disease isolates stored in memory accessible by the at least one processing unit, and Comparing at least one reference sequence stored in a database accessible by one processing unit to determine a variant between the infectious disease isolate sequence and the at least one reference sequence; Determining the evolutionary distance of the infectious disease isolate from the at least one reference sequence based at least in part on the variant using one processing unit; and using the at least one processing unit, the infection Stored in the database from the evolutionary distance of the disease isolate and the at least one reference sequence. Comparing the distribution of evolutionary distances of the plurality of sequences and based on at least in part the difference between the evolutionary distance of the infectious disease isolate and the distribution of evolutionary distances of the plurality of sequences. Determining whether the isolate was transmitted by the first reservoir or the second reservoir, and determining whether the infectious disease isolate was transmitted by the first reservoir or the second reservoir Providing to a user using a display. The determination of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir is such that the evolutionary distance of the infectious disease isolate is the distribution of the evolutionary distances of the plurality of sequences. Can be based at least in part on whether they fall within the desired confidence interval.

  According to an exemplary embodiment of the present invention, a system includes a processing unit, a memory accessible by the processing unit, a database accessible by the processing unit, and a display coupled to the processing unit. And the processing unit compares the infectious disease isolate sequence stored in the memory with at least one reference sequence stored in the database, and the infectious disease isolate sequence and the at least one reference sequence. And determining the replication rate of the infectious disease isolate based at least in part on the variant, the replication rate of the infectious disease isolate and the replication rate of the at least one reference sequence, And the difference between the replication rate of the infectious disease isolate and the replication rate of the at least one reference sequence is at least Based in part on determining whether the infectious disease isolate is transmitted by the first reservoir or the second reservoir, the infectious disease isolate is determined by the first reservoir or the second reservoir. It is configured to provide the display with the above determination of whether it has been communicated. The system further comprises a computer system accessible by the processing unit, wherein the processing unit determines the determination of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir. Can be configured to provide. The system can also include a sequencing unit configured to provide the array of the infectious disease isolate to the memory.

FIG. 6 is a block diagram of a transfer vector according to an embodiment of the present disclosure. 3 is a phylogenetic tree according to an embodiment of the present disclosure. 3 is a dated phylogenetic tree according to an embodiment of the present disclosure. 3 is a flowchart of a method according to an embodiment of the present disclosure. 1 is a block diagram of a system according to an embodiment of the system. 4 is a graph of a growth rate curve according to an embodiment of the present disclosure. 4 is an empirical cumulative distribution function plot according to an embodiment of the present disclosure. 3 is a density plot according to an embodiment of the present disclosure. It is a flowchart of the process by embodiment of this invention.

  The following description of certain exemplary embodiments is merely exemplary in nature and is in no way intended to limit the invention or its application or uses. In the following detailed description of embodiments of the present system and method, reference is made to corresponding drawings that form a part hereof, and in the drawings, the specific embodiments in which the above-described systems and methods can be implemented. Is illustrated. These embodiments are described in sufficient detail to enable those skilled in the art to practice the systems and methods of the present disclosure, other embodiments can be utilized, and structural and logical changes can be made. It should be understood that this can be done without departing from the spirit and scope of the present system.

  The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present system is defined only by the appended claims. The leading digit of a reference number in the drawings of this document generally corresponds to the drawing number, with the exception that identical elements that appear in multiple drawings are identified by the same reference number. Further, for the sake of clarity, a detailed description of particular features will not be given when it will be apparent to those skilled in the art that the description of the system is not ambiguous.

  Infectious diseases can be caused by pathogens such as bacteria, viruses, fungi, parasites or other microorganisms. Some infections may be caused by multiple types of microorganisms present at the same time. Infectious diseases can be spread by various transfer vectors. An exemplary transfer vector is shown in FIG. In some examples, the infection can be transmitted between two living microorganisms. For example, a physician can treat a first patient with an infection. If the doctor does not completely disinfect his hand, he may transmit the infection from the first patient to the second patient. This example can correspond to the transfer vector 100. An infected microorganism can also transmit the infection directly to another microorganism. For example, an infected person may sneeze or cough near another person. This person inhales the pathogen and then becomes infected. This example can correspond to the transfer vector 105. In other examples, the infection can be transmitted from non-living areas to living microorganisms. The non-living area can be a surface such as a table or a sink counter. The non-biological region may be a medical device such as a dialysis machine or an endoscope. For example, a patient may have an infection when an injury opened on the patient contacts a non-sterile test table. This example is shown as transfer vector 110.

  Determining the transfer vector (eg, how the patient was infected) can allow the infection to be traced back to its source. The source can then be removed to prevent further transmission of the infection. For example, if the source is a patient, the patient can be isolated to avoid infecting other patients until the infection can be cleared with treatment (eg, with antibiotics). In one example, if the source is equipment, this equipment can be sterilized or replaced with new equipment. The ability to track infections to their source in a hospital environment can reduce the occurrence of HAI and associated costs. It can also reduce the time and cost to unnecessarily treat areas not associated with HAI with disinfectants.

  When an infection such as HAI is detected, a sample can be collected by medical staff from a patient, surface, food, equipment, or other suspected source. The sample can include tissue, blood, water, surface cotton. The sample can then be processed to separate the pathogen causing the infection from other substances in the sample. Infectious disease isolates can then be analyzed by various methods. The analysis can determine the pathogen type, species, drug resistance and / or other characteristics. Although this analysis can help determine an effective treatment, it cannot adequately identify the transfer vector.

  By collecting infectious disease isolates from infected microorganisms or non-living areas and analyzing their gene sequences, the transmission vector of the infectious disease can be determined using phylogenetic methods. Infectious disease isolates are elements of a sample that contain genetic information from pathogens. Phylogenetics is the study of evolutionary relationships between microorganisms. Such a relationship is often represented as a weighted graph, for example a tree. Examples of phylogenetic trees are shown in FIGS. 2A-2B. Phylogenetic methods analyze all or part of a microbial gene sequence. By determining the evolutionary history of an infection, the infection can be traced back to its source. Evolutionary history can provide an understanding of how different incidents of infectious diseases are or are not associated. For example, the sequences of infectious disease isolates from multiple infected patients can be compared. It can be determined when in time the patient became infected. It can also be determined that one or more patients were infected by different sources.

で発生することができる。 There are several phylogenetic methods. This includes evolutionary distances, parsimonious and maximum likelihood based methods. Distance-based methods are those in which the evolutionary distance is calculated between each microorganism. The evolutionary distance is calculated based on the degree of similarity between the microbial gene sequences. One such method for determining the evolutionary distance is called the Juke-Cantor method (TH Jukes, CR Cantor, “Evolution of protein molecules in Mammalian protein metabolism” edited by MN Munro, Vol. III (1969). ), Pp. 21-132), where a transition from any particular nucleotide in the genome to another nucleotide, ie a transition or transversion, has the same probability

Can occur.

として与えられる。 In Equation 1 above, the instantaneous rate matrix Q represents the rate of change between a pair of nucleotides per instant of time. The probability transition matrix P is

As given.

となる。 As a result, the evolutionary distance between any two microorganisms under this model is simply

It becomes.

となる。 Where p is the number of sites along different single nucleotide polymorphisms (SNPs) / DNA between sequences. As p approaches the equilibrium value (75% of the sites are different), the distance goes to infinity. This simple model, however, is a biological consideration that transitions (purine vs. purine (ag) or pyrimidine vs. pyrimidine (t-c)) and transversion (purine vs. pyrimidine or vice versa) occur at different rates. Is not considered. Another distance model, the Kimura two-parameter model ("A simple method for controlling evolutionary rates of base substitutions through comparative studies of nucleotide sequences" by Kimura, Motoo, Journal of molecular evolution 16.2 (1980): 111-120) Attempt to fix. in this case,

It becomes.

  p is the transition ratio and q is the transversion ratio.

  To determine their evolutionary distance, once the infection isolate sequences are compared, the rate of evolution can be determined. Evolutionary distances and relationships between infectious disease isolates from the sample can then be plotted in a graphical format, for example a tree plot. Neighbor joins (Saitou N, Nei M's "The neighbor-joining method: a new method for reconstructing phylogenetic trees", Molecular Biology and Evolution, volume 4, issue 4, pp. 406-425, July 1987) (Unrooted) A way to build wood. This method corrects the rate of unequal evolution between sequences by first searching for a pair of adjacent leaves i and j with the same parent node k. That is, leaves i and j can be pathogens evolved from a common pathogen k. Leaves i and j are then removed from the list of leaf nodes and k can be added to the current list of nodes. The node distance is then recalculated. This algorithm is an example of a greedy “minimum evolution” algorithm.

  Using the tree representation of many infectious disease isolate sequence samples, the relative timing of one infection to another can be estimated. Without loss of generality, a method called mean path length (MPL) can be used (Britton, Tom et al. "Phylogenetic dating with confidence intervals using mean path lengths", Molecular phylogenetics and evolution 24.1 (2002): 58-65). The MPL method estimates the age of a node having an average distance from a node to all leaves descending from this node. Under the assumption of a similar molecular clock, ie the rate of evolution, the standard error of the estimated node age can be calculated. Using this method, mutation rates can be calculated for different infectious disease isolates.

  The source of infection can be determined based on the replication rate. Pathogens can replicate at different rates in different environments. Different environments that can have reservoirs of pathogens that replicate at different rates include, but are not limited to, blood, saliva, food, surgical tables, sinks, toilets, and bed linens. The replication rate can be correlated with the mutation rate. Replication rate, total replication, mutation rate, total nucleotide change, other metrics that represent a measure of phylogenetic relationship, phylogenetic status, sample reproduction or replication history, in addition to the metrics represented in this document or Can alternatively be used. As such, any phylogenetic metric, measure, indicator or predictor is within the scope of the present invention and will be referred to hereinafter as a phylogenetic metric. In general, the mutation rate is lower for pathogens, which replicates at a lower rate. If the replication rate of the pathogen is known with respect to the environment, based on the calculated mutation rate, it can be determined that the infectious disease isolate originated from that environment. For example, pathogens can replicate more rapidly in a fluid environment such as blood than in a dry environment such as furniture surfaces. If an infectious disease isolate taken from a patient exhibits a high mutation rate compared to a reference infectious disease isolate, it can be determined that the patient has transmitted the infection from another living microorganism. This decision may allow hospital staff to focus on trying to contain infections in other patients, rather than testing equipment for contamination. This can allow hospital staff to reduce the time to determine the source of infection and save the cost of unnecessarily disinfecting equipment.

  FIG. 3 shows a flowchart of a method 300 for determining the source of an infection according to an embodiment of the present disclosure. In step 305, the medical staff may first collect samples from different environments to obtain an infectious disease isolate or multiple infectious disease isolates. Samples can be collected on a daily basis or can be collected based on the identified HAI. In step 310, the infectious disease isolate can be processed and sequenced based on sequencing techniques known in the prior art. Examples of companies that provide sequencing technology include 454 Life Sciences, Roche and Pacific Biosciences. Sequencing techniques known in the prior art can allow the entire genome of an infectious disease isolate to be sequenced. The hospital can have sequencing technology on site or the hospital can send the sample to another sequencing company. A digital representation of the sequence can be generated and stored in memory accessible by one or more processing units allowing analysis of the sequence. Unless otherwise stated, it is envisioned that any comparison, analysis or determination based on a gene sequence is performed by one or more processing units. In step 315, the infectious disease isolate sequence can be compared against one or more sequences by the processing unit. Other sequences can be sequences from other collected infectious disease isolates, reference sequences of known pathogens from public or private databases, and / or sequences from other sources. The comparison can include determining a variant between the infectious disease isolate sequence and one or more other sequences. Hereinafter, variants or gene variants refer to single nucleotide differences or gene level differences. Variants can be found using existing software tools such as BWA-samstools and Golden Helix.

  In step 320, these variants can be used to determine the evolutionary history of the infection isolate sequence for one or more sequences. For example, it can be envisaged that a given infectious substance exhibits single nucleotide mutations at similar rates across all transmission regions that are living or non-living. Consequently, a cumulative number of single nucleotide changes can be used to estimate the total number of sequence replication occurrences, ie the total number of generations. As such, a further conclusion can be made that the total number of variations or generations in evolutionary history can be attributed to the type of transmission region. The history of evolution can be determined by one of the methods described above or another method. In step 325, the mutation rate of the infectious disease isolate is calculated based on the history of evolution. The rate of mutation can be calculated by one of the methods described above or another method.

  According to one exemplary embodiment, in step 330, the rate of mutation of the infectious disease isolate is compared against the rate of mutation of one or more other sequences. In step 335, a source of infection is determined based on the mutation rate comparison. Infectious disease isolate sequences and other sequences can be clustered by mutation rate, with each cluster assigned to a different infectious disease source.

  According to another exemplary embodiment, at step 330, the rate of replication of the infectious disease isolate is compared against the rate of replication of one or more other sequences. In step 335, a source of infection is determined based on the comparison of replication rates. Infectious disease isolate sequences and other sequences can be clustered by replication rate, with each cluster assigned to a different infectious disease source. Infectious disease isolate sequences can be compared against reference sequence replication rates from different known environments and assigned a source environment as described below. Other methods of determining the classification of the infectious disease source or the infectious disease source of the infectious disease isolate may be performed.

  An example of a system 400 used to determine the source of infection transmission according to certain embodiments of the present disclosure is shown as a block diagram in FIG. A digital form of the infectious disease isolate sequence can be included in the memory 405. Memory 405 may be accessible by processing unit 415. The processing unit 415 can include one or more processing units. The processing unit 415 can have access to a database 410 that includes one or more arrays. Processing unit 415 may provide the results of the determination to display 820 and / or database 410. Display 420 may be an electronic display that is visible to the user. Optionally, the processing unit 415 can further access the computer system 425. The computer system 425 can include additional databases, memory, and / or processing units. Computer system 425 can be part of system 400 or can be remotely accessed by system 400. In some embodiments, the system 400 can also include a sequencing unit 430. The sequencing unit 430 can process the infectious disease isolate to generate a sequence and generate an infectious disease isolate sequence in digital form.

  2A-2B illustrate examples according to certain embodiments of the present disclosure. In this example, 10 HAI samples can be collected from various reservoirs in similar or different environments, and the entire genome for the infectious disease isolate can be sequenced. Variants can be determined and evolutionary distances can be calculated. Based on these evolutionary distances, the original tree 200 can be plotted as shown in FIG. 2A. In this example, the original tree 200 was generated using an adjacent connected tree method based on Kimura two-parameter distance estimation. Tree 200 shows evolutionary distances and relationships between 10 HAIs. The length of the branch is proportional to these calculated distances. For example, node 11 and node 12 corresponding to two different HAIs have an evolutionary distance of 0.72. As mentioned above, this is a measure of similarity between two HAIs. The greater the distance of evolution, the lower the similarity between the two HAI sequences. The relative age in time for each node / HAI sample can be calculated based on the evolutionary distance original tree 200 by using a date method such as the MPL method described above. A dated tree 205 is shown in FIG. 2B. In this example, in the original tree 100, the edge length from the 11th node to the 12th node is 0.72, and the edge length from the 12th node to the node / leaf t10 is 0.99. is there. If the age of a particular node is known, the age of the remaining nodes can be estimated. In this example, the age of the eleventh node is known and is a common ancestor for all other nodes in the tree. The MPL statistic for the eleventh node is 1.56. If node 11 branches at least two days ago, the remaining nodes can be converted to the minimum age in the day by dividing, so that 0.78 = 1.56 / 2. For example, using this formula for age, node 12 has branched from node 11 1.479 days ago.

  With this date information, it is expected that a sample can have a small number of mutations for a particular environment. If the evolutionary distance is high compared to another sample or reference sequence and / or if the calculated mutation or replication rate is higher compared to another sample or reference sequence, it corresponds to that sample Infectious diseases can be determined to be transmitted from an environment where a high replication rate of the pathogen is enabled. High replication rates can allow greater probability and occurrence for mutations, which increases the difference between sequences of infectious disease isolates collected at different time points. For example, a bacterial sequence having a large evolutionary distance from another bacterial sequence can be determined to have been transmitted by a living microorganism. Living microorganisms can provide more nutrients and maintain higher replication rates with respect to pathogens than non-living areas. Thus, infectious disease isolates exhibiting evolutionary distances above or below a desired threshold, the occurrence of cumulative mutations, mutation rates, or combinations thereof can be determined to have been transmitted by a particular source. .

  Alternatively or additionally to the methods used above, the pathogen replication or growth rate for one or more environments can be known. An exemplary plot 500 of growth rate according to certain embodiments of the present disclosure is shown in FIG. 5A. Based on the known growth rate, a specific number of mutations per generation can be expected.

  Referring to FIG. 5B, according to one exemplary embodiment, the phylogenetic closest neighbor is investigated by comparing the sequence of this sample with the sequence of past samples stored in the database. Can be determined for sample 520 in the middle. Once the nearest neighbor is identified, the number of differences (normalized to the total number of nucleotide groups being compared) can be estimated. Under the assumption of a common mutation rate per replication cycle for this microorganism, characteristic mutation curves are plotted for multiple reservoirs (eg, reservoirs 1, 2, and 3 shown in FIG. 5B). Can do. Mutation curves can be selected based on the replication rate of this microorganism in different reservoirs, ie transmission regions. Based on the chronological time difference between the sample under study and its determined nearest neighbor isolate, the expected number of accumulated mutations is estimated for different growth rates. The actual growth rate closest to the observed mutation can be identified as the growth rate of the sample, and the reservoir known to be associated with this growth rate is the most likely source of transmission (Figure Can be identified as reservoir 2) for sample 520 in 5B.

  An infectious disease isolate can be fitted to a growth rate curve based on its estimated growth rate. For example, if an infectious disease isolate is found to have a low growth rate (eg, 0.2) and fits curve 505, it can be determined that the infectious disease has been transmitted by the surface. If the infectious disease isolate is found to have an intermediate growth rate (eg, 0.5) and fits the curve 510, it can be determined that the infectious disease has been transmitted by a moist environment, eg, a toilet. If the infectious disease isolate is found to have a high growth rate (eg, 1.0) and fits the curve 515, it can be determined that the infectious disease isolate has been transmitted by a living microorganism.

  In addition or alternatively to the method used above, the evolutionary distance distribution of the infectious disease isolate sample and / or reference sequence can be estimated. The evolutionary distance of a new infectious disease isolate sample can be compared against the evolutionary distance of a known reference sequence or the evolutionary distance of a previously analyzed infectious disease isolate sample. An empirical cumulative distribution function (ECDF) can be generated using known statistical methods. An exemplary ECDF plot 600 according to an embodiment of the present disclosure is shown in FIG. In this example, if it is determined that the infectious disease isolate falls outside the desired confidence interval (eg, 95%), the infectious disease isolate is determined to have been transmitted from a different source than the reference sequence. Can do. In the plot shown in FIG. 6, any infectious disease isolate sequence with x> 0.8 can be determined to have a high mutation rate compared to the reference sequence, thus the infectious disease is It can be determined that it has been transmitted by a living microorganism.

  FIG. 7 illustrates different methods according to certain embodiments of the present disclosure for clustering sequences based on evolutionary distances. Despite being represented in a different graphic format, such as kernel density plot 700, the method is similar to that represented with respect to FIG. If the infectious disease isolate sequence falls outside the desired confidence interval for the evolutionary distance of the reference sequence, the infectious disease isolate sequence is determined to have been transmitted by a source different from the source of the reference sequence. In plot 700, infectious disease isolates with an evolutionary distance of 0.2 or greater can be determined to have been transmitted by living microorganisms when the relative age is low.

  The reference sequence is grouped into a single cluster in the examples shown in FIGS. 6 and 7, but it can have multiple clusters of reference sequences. Each cluster can represent the evolutionary distance for pathogens in a particular environment. Confidence intervals for new infectious disease isolates belonging to each cluster can then be calculated using known statistical methods. The source of infection transmission can be determined based on which cluster the infection isolate sequence has the highest probability of inclusion.

  FIG. 8 shows a flowchart summarizing an exemplary process 800A and 800B according to an embodiment of the present disclosure for determining a source of infection transmission. Process 800A and / or 800B may be included in step 335 of method 300 in FIG. Step 335 of the method 300 may include one or more processes that determine the source of infection transmission. Process 800A determines whether the infectious disease source is the first reservoir or the second reservoir based on whether the mutation rate of the infectious disease isolate is greater than or less than the desired threshold X. Process 800B determines whether the infectious disease source is the first reservoir or the second reservoir based on whether the evolutionary distance of the infectious disease isolate is included in the confidence interval X. The confidence interval can be based on the distribution of one or more sample sequences. Other processes can also be performed. Although only two reservoirs are shown, embodiments of the present disclosure can include making a decision between any number of reservoirs. For example, in process 800A, the value X can be replaced by a plurality of values that define a range of mutation rates. Each range can be associated with a different reservoir.

  Once the determination of the source of transmission of the infection is made by one or more processing units, the user, database and / or computer may be used by at least one processing unit based on the infection isolate sequence stored in memory. Decisions can be provided for the system. The user can be a member of an infectious disease control staff in a hospital. A user can receive a visual indicator on an electronic display coupled to the processing unit. The user can use the infection source determination to adjust the burden on the infection control staff to take steps to isolate and remove the source of infection. For example, if the infection source is determined to be from a living organism such as a particular patient, the infection control staff can isolate the patient and other patients after the nurse and doctor treat the patient It can be ensured that advanced sterilization methods are used before contacting with. If it is determined that the infectious disease source is from a non-biological area, such as a bronchoscope, the equipment can be disinfected and retested for pathogens before being used in additional patients.

  It can be determined that multiple infectious disease isolates are all from different unrelated sources. In these examples, the infection control staff can determine that an aseptic procedure and / or infection control protocol has been broken at a healthcare facility. Retraining medical staff for further analysis and / or appropriate procedures to reduce transmission of infection can be performed.

  The determination and infectious disease isolate sequences can be stored in a database for use in determining future infectious disease sources. The data can also be transferred to a computer system accessible by additional users, hospitals or agencies. This allows easier information sharing and can improve infection control. It can also allow easier reporting of infections. This may be required by regulation. For example, the processing unit can automatically generate a report with the decision and can provide the report to an agency that is tracking infectious diseases, such as the US Centers for Disease Control (CDC).

  Of course, any one of the above embodiments or methods can be combined or separated from one or more other embodiments and / or methods and / or separate devices according to the present systems, devices and methods. Alternatively, it should be understood that it can be performed between device portions.

  Finally, the above description is intended to be merely illustrative of the present system and should not be construed to limit the scope of the appended claims to any particular embodiment or group of embodiments. Thus, while the system has been described in specific detail with reference to exemplary embodiments, numerous modifications and alternative embodiments have been described in the broader scope of the system as set forth in the claims below and It should also be understood that it can be devised by those skilled in the art without departing from the intended spirit and scope. Accordingly, the specification and drawings are to be understood in an illustrative manner and are not intended to limit the scope of the appended claims.

Claims (24)

In one way,
Receiving electronic data representing an infectious disease isolate sequence;
Comparing the electronic data representative of the infectious disease isolate sequence with at least one reference sequence stored in a database to determine a variant between the infectious disease isolate sequence and the at least one reference sequence; ,
Determining at least part of the evolutionary history of the infectious disease isolate based at least in part on the variant; and
Calculating a phylogenetic metric of the infectious disease isolate based at least in part on the evolutionary history;
Comparing the phylogenetic metric of the infectious disease isolate with the phylogenetic metric of the at least one reference sequence;
Based at least in part on the difference between the phylogenetic metric of the infectious disease isolate and the phylogenetic metric of the at least one reference sequence, the infectious disease isolate comprises a first reservoir or a second Determining whether it has been transmitted by a reservoir of
Providing an indication of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir.   The indication provided is based at least in part on the determination of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir, and the first reservoir or second The method according to claim 1, wherein the method is for isolating a reservoir of water.   The method of claim 1, wherein the indication is text on an electronic display.   The method of claim 1, wherein determining at least a portion of the evolutionary history comprises calculating an evolutionary distance.   5. The method of claim 4, wherein the evolutionary distance is calculated by the Juke-Cantor method.   The method of claim 1, wherein the phylogenetic metric is a mutation rate calculated by an average path length method. In one way,
Using at least one processing unit, an array of infectious disease isolates stored in memory accessible by the at least one processing unit and at least one stored in a database accessible by the at least one processing unit Comparing a reference sequence and determining a variant between the infectious disease isolate and the at least one reference sequence;
Using the at least one processing unit to determine a replication rate of the infectious disease isolate based at least in part on the variant;
Comparing the replication rate of the infectious disease isolate with the replication rate of the at least one reference sequence using the at least one processing unit, and the replication rate of the infectious disease isolate and the at least one reference sequence; Determining whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir based at least in part on the difference in the replication rate of
Providing the user with a display using the display to determine whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir.   The method according to claim 7, wherein the first storage unit is a biological microorganism, and the second storage unit is a non-biological region.   9. The method of claim 8, further comprising providing a notification to the user to disinfect equipment if it is determined that the infectious disease isolate has been transmitted by the non-living area.   9. The method of claim 8, further comprising providing a notification to the user to test equipment for the infectious disease isolate if it is determined that the infectious disease isolate has been transmitted by the non-living area.   9. The method of claim 8, further comprising providing a notification to the user to test a patient for the infectious disease isolate if it is determined that the infectious disease isolate has been transmitted by the living microorganism.   9. The method of claim 8, further comprising providing a notification to the user to isolate a patient if it is determined that the infectious disease isolate has been transmitted by the living microorganism.   Generating a report of the determination of whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir and sending it to an agency tracking the infection; The method of claim 7. In one way,
Using at least one processing unit, an array of infectious disease isolates stored in memory accessible by the at least one processing unit and at least one stored in a database accessible by the at least one processing unit Comparing a reference sequence and determining a variant between the infectious disease isolate and the at least one reference sequence;
Using the at least one processing unit to determine the evolutionary distance of the infectious disease isolate from the at least one reference sequence based at least in part on the variant;
Comparing the evolutionary distance of the infectious disease isolate with the distribution of evolutionary distances of a plurality of sequences stored in the database from the at least one reference sequence using the at least one processing unit; Based on the difference between the evolutionary distance of the infectious disease isolate and the distribution of the evolutionary distances of the plurality of sequences, the infectious disease isolate is transmitted by the first reservoir or the second reservoir. Determining what has been done;
Providing the user with a display using the display to determine whether the infectious disease isolate has been transmitted by the first reservoir or the second reservoir.   The determination of whether the infectious disease isolate was transmitted by the first reservoir or the second reservoir is such that the evolutionary distance of the infectious disease isolate is the distribution of evolutionary distances of the plurality of sequences. 15. The method of claim 14, wherein the method is based at least in part on whether it falls within a desired confidence interval.   The method of claim 15, wherein the confidence interval is 95%.   15. The method of claim 14, wherein the distribution of evolutionary distances of the plurality of sequences is a plurality of distributions based on the evolutionary distance of the plurality of sequences.   A first one of the plurality of distributions based on the evolutionary distance of the plurality of sequences corresponds to the first reservoir, and a second of the plurality of distributions based on the evolutionary distance of the plurality of sequences. The method of claim 17, wherein one of the two corresponds to the second reservoir.   The determination of whether the infectious disease isolate was transmitted by the first reservoir or the second reservoir is based on the evolutionary distance of the plurality of sequences. The method of claim 18, wherein the method is based at least in part on the probability of whether the second one includes the evolutionary distance of the infectious disease isolate.   As one of the plurality of sequences, the infectious disease isolate sequence is stored in the database for use in future determinations as to whether a new infectious disease isolate has been transmitted by the first reservoir or the second reservoir. The method of claim 14, further comprising storing. A system,
A processing unit;
Memory accessible by the processing unit;
A database accessible by the processing unit;
A display coupled to the processing unit;
The processing unit is
Comparing the sequence of the infectious disease isolate stored in the memory with at least one reference sequence stored in the database to determine a variant between the infectious disease isolate sequence and the at least one reference sequence;
Determining a replication rate of the infectious disease isolate based at least in part on the variant;
Comparing the replication rate of the infectious disease isolate with the replication rate of the at least one reference sequence, and at least partly differing between the replication rate of the infectious disease isolate and the replication rate of the at least one reference sequence On the basis of determining whether the infectious disease isolate was transmitted by the first reservoir or the second reservoir,
A system configured to provide the display with the determination of whether the infectious disease isolate has been delivered by the first reservoir or the second reservoir. A computer system accessible by the processing unit;
The system of claim 21, wherein the processing unit is configured to provide the determination of whether the infectious disease isolate has been transmitted by the first reservoir or a second reservoir.   The system of claim 21, further comprising a sequencing unit configured to provide the array of the infectious disease isolate to the memory.   The system of claim 21, wherein the processing unit comprises a plurality of processing units.

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